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Books > Computing & IT > Applications of computing > Artificial intelligence
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Reinforcement Learning - State-of-the-Art (Hardcover, 2012 ed.)
Loot Price: R9,196
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Reinforcement Learning - State-of-the-Art (Hardcover, 2012 ed.)
Series: Adaptation, Learning, and Optimization, 12
Expected to ship within 10 - 15 working days
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Reinforcement learning encompasses both a science of adaptive
behavior of rational beings in uncertain environments and a
computational methodology for finding optimal behaviors for
challenging problems in control, optimization and adaptive behavior
of intelligent agents. As a field, reinforcement learning has
progressed tremendously in the past decade. The main goal of this
book is to present an up-to-date series of survey articles on the
main contemporary sub-fields of reinforcement learning. This
includes surveys on partially observable environments, hierarchical
task decompositions, relational knowledge representation and
predictive state representations. Furthermore, topics such as
transfer, evolutionary methods and continuous spaces in
reinforcement learning are surveyed. In addition, several chapters
review reinforcement learning methods in robotics, in games, and in
computational neuroscience. In total seventeen different subfields
are presented by mostly young experts in those areas, and together
they truly represent a state-of-the-art of current reinforcement
learning research. Marco Wiering works at the artificial
intelligence department of the University of Groningen in the
Netherlands. He has published extensively on various reinforcement
learning topics. Martijn van Otterlo works in the cognitive
artificial intelligence group at the Radboud University Nijmegen in
The Netherlands. He has mainly focused on expressive knowledge
representation in reinforcement learning settings.
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